• Offered fully online - you can study from anywhere in the world according to your own schedule;

• High level of support - instructors are available on Zoom and via email, student-to-student communication is carried out on Slack and Coursera forums. Live sessions are hosted on a regular basis, students can always discuss their questions and ideas between each other and with the Teaching Staff, there are many assignments checked by instructors manually. 

• Lots of practical assignments - almost every course ends up with the final project. In addition, the programme includes 3 big projects which allow students to work on the real business or industry relevant tasks provided by the partners of the programme and to get hands-on experience;

• Opportunity to be interviewed by industry partners of the programme for students with the highest academic performance;

• The programme is organised according to demands and expertise of the leading IT companies presented in Russia;

• Students without previous math and/or programming experience are able to complete the programme successfully with sufficient time investment.

Graduates can start or continue their career in the fields like data science, machine learning, analytics and apply for Junior Data Scientist or Junior Machine Learning Engineer positions. Besides, graduates can continue their academic career as PhD students and do research in the field of data science.

In the framework of the programme students can choose one out of three tracks - two of them are industry relevant which aim to prepare students for specific positions, and one is for research goals:

• Data Scientist,

• Machine Learning Engineer,

• Researcher in Data Science.

From the beginning of the first semester students learn programming (Python, SQL), algorithms and data structures, mathematics for data analysis. The programming and math blocks end up with the project on collecting and processing big data. In the second semester students choose a Track.

Apart from standard courses which combine theory and practice, there are also 2 project courses: Machine Learning and Final Project (Master’s Thesis which can be devoted to practical or research problems). 

In order to complete the programme successfully, students must earn 120 ECTS credits. The learning process is offered fully online and is monitored by standard tools for online education: daily communication on forums and during the webinars, exams with proctoring, projects and thesis defense via Zoom.

This degree programme of HSE University is adapted for students with special educational needs (SEN) and disabilities. Special assistive technology and teaching aids are used for collective and individual learning of students with SEN and disabilities. The specific adaptive features of the programme are listed in each subject's full syllabus and are available to students through the online Learning Management System.

All documents of the degree programme are stored electronically on this website. Curricula, calendar plans, and syllabi are developed and approved electronically in corporate information systems. Their current versions are automatically published on the website of the degree programme. Up-to-date teaching and learning guides, assessment tools, and other relevant documents are stored on the website of the degree programme in accordance with the local regulatory acts of HSE University.

I hereby confirm that the degree programme documents posted on this website are fully up-to-date.

Vice Rector Sergey Yu. Roshchin

Summary of Degree Programme 'Master of Data Science'